Macarthur, Kathryn, Stranders, Ruben, Ramchurn, Sarvapali and Jennings, Nick
A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems
At Twenty-Fifth Conference on Artificial Intelligence (AAAI), United States.
07 - 11 Aug 2011.
We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.
Conference or Workshop Item
||Event Dates: August 7-11, 2011
|Venue - Dates:
||Twenty-Fifth Conference on Artificial Intelligence (AAAI), United States, 2011-08-07 - 2011-08-11
||Agents, Interactions & Complexity
|7 August 2011||Published|
||28 Apr 2011 11:16
||17 Apr 2017 17:57
|Further Information:||Google Scholar|
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